Rancang Bangun Aplikasi Pengawasan Ujian Online (iProctor) untuk Pengawas dan Peserta Ujian

Sugianto, Daniel (2022) Rancang Bangun Aplikasi Pengawasan Ujian Online (iProctor) untuk Pengawas dan Peserta Ujian. Project Report. [s.n.], [s.l.]. (Unpublished)

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Abstract

Pandemi COVID-19 telah mengubah banyak hal dalam kehidupan manusia. Aktivitas yang umumnya dilakukan secara offline telah berubah menjadi online. Pelaksanaan ujian merupakan salah satu aktivitas yang mengalami perubahan tersebut. Pelaksanaan ujian secara online menimbulkan permasalahan baru, yaitu bagaimana cara mengawasi semua siswa agar ujian dapat berjalan dengan jujur.
Aplikasi iProctor dirancang untuk menyelesaikan permasalahan tersebut. Aplikasi iProctor Student akan mengawasi siswa dengan memanfaatkan teknologi deteksi ucapan dan pengenalan wajah. Selanjutnya, aplikasi iProctor Proctor akan menampilkan hasil deteksi kecurangan setiap siswa kepada pengawas dalam bentuk probabilitas kecurangan.
Aplikasi iProctor dibuat menggunakan bahasa pemrograman Python, library Tkinter untuk antarmuka pengguna, library face-recognition untuk pengenalan wajah, dan library py-webrtcvad untuk deteksi ucapan.
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The COVID-19 pandemic has changed many things in human life. Activities that are generally done offline have turned into online. Exam is one of the activities that is affected by the pandemic. Online exam raises new problems, namely how to supervise all students so that exam can be done without cheating.
The iProctor application is designed to solve that problem. The iProctor Student app will keep an eye on students by utilizing speech detection and facial recognition technologies. Furthermore, the iProctor Proctor application will display the results of each student's detection to the supervisor in the form of the probability of cheating.
The iProctor application is built using the Python programming language, the Tkinter library for the user interface, the face-recognition library for facial recognition, and the py-webrtcvad library for speech detection.

Item Type: Monograph (Project Report)
Uncontrolled Keywords: python, tkinter, face recognition, speech detection, pengenalan wajah, deteksi ucapan
Subjects: Q Science > Q Science (General) > Q325.5 Machine learning. Support vector machines.
Divisions: Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering
Depositing User: Daniel Sugianto
Date Deposited: 28 Jun 2022 01:44
Last Modified: 28 Jun 2022 01:44
URI: http://repository.its.ac.id/id/eprint/94926

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